diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 781b3b2282a87..ad96818b6b300 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -362,6 +362,7 @@ Datetimelike
 - Bug in :class:`Timestamp` constructor failing to raise when ``tz=None`` is explicitly specified in conjunction with timezone-aware ``tzinfo`` or data (:issue:`48688`)
 - Bug in :func:`date_range` where the last valid timestamp would sometimes not be produced (:issue:`56134`)
 - Bug in :func:`date_range` where using a negative frequency value would not include all points between the start and end values (:issue:`56382`)
+- Bug in :func:`infer_freq` prevented application to :class:`Series` of with ``pyarrow`` dtype. (:issue:`58403`)
 - Bug in :func:`tseries.api.guess_datetime_format` would fail to infer time format when "%Y" == "%H%M" (:issue:`57452`)
 - Bug in setting scalar values with mismatched resolution into arrays with non-nanosecond ``datetime64``, ``timedelta64`` or :class:`DatetimeTZDtype` incorrectly truncating those scalars (:issue:`56410`)
 
diff --git a/pandas/tests/tseries/frequencies/test_inference.py b/pandas/tests/tseries/frequencies/test_inference.py
index edfc1973a2bd9..05bfdff808d37 100644
--- a/pandas/tests/tseries/frequencies/test_inference.py
+++ b/pandas/tests/tseries/frequencies/test_inference.py
@@ -554,3 +554,27 @@ def test_infer_freq_non_nano_tzaware(tz_aware_fixture):
 
     res = frequencies.infer_freq(dta)
     assert res == "B"
+
+
+@pytest.mark.parametrize(
+    ("data", "expected"),
+    [
+        (["2022-01-01T10:00:00", "2022-01-01T10:00:30", "2022-01-01T10:01:00"], "30s"),
+        (["2022-01-01T10:00:00", "2022-01-01T10:00:37", "2022-01-01T10:01:00"], None),
+        (["2022-01-01T10:00:00", "2022-01-01T10:00:01", "2022-01-01T10:00:02"], "s"),
+        (
+            [
+                "2022-01-01T10:00:00",
+                "2022-01-01T10:00:01",
+                "2022-01-01T10:00:02",
+                "2022-01-01T10:00:04",
+            ],
+            None,
+        ),
+    ],
+)
+@pytest.mark.parametrize("cls", [Index, Series])
+def test_infer_freq_pyarrow(data, expected, cls):
+    pytest.importorskip("pyarrow")
+    obj = cls(data).astype("timestamp[s][pyarrow]")
+    assert frequencies.infer_freq(obj) == expected
diff --git a/pandas/tseries/frequencies.py b/pandas/tseries/frequencies.py
index 534bee5fede44..10d5506466186 100644
--- a/pandas/tseries/frequencies.py
+++ b/pandas/tseries/frequencies.py
@@ -33,10 +33,7 @@
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.common import is_numeric_dtype
-from pandas.core.dtypes.dtypes import (
-    DatetimeTZDtype,
-    PeriodDtype,
-)
+from pandas.core.dtypes.dtypes import PeriodDtype
 from pandas.core.dtypes.generic import (
     ABCIndex,
     ABCSeries,
@@ -112,20 +109,16 @@ def infer_freq(
     >>> pd.infer_freq(idx)
     'D'
     """
+    from pandas.api.types import is_datetime64_any_dtype
     from pandas.core.api import DatetimeIndex
 
-    if isinstance(index, ABCSeries):
-        values = index._values
-        if not (
-            lib.is_np_dtype(values.dtype, "mM")
-            or isinstance(values.dtype, DatetimeTZDtype)
-            or values.dtype == object
-        ):
-            raise TypeError(
-                "cannot infer freq from a non-convertible dtype "
-                f"on a Series of {index.dtype}"
-            )
-        index = values
+    if isinstance(index, ABCSeries) and not (
+        is_datetime64_any_dtype(index) or index.dtype == object
+    ):
+        raise TypeError(
+            "cannot infer freq from a non-convertible dtype "
+            f"on a Series of {index.dtype}"
+        )
 
     inferer: _FrequencyInferer