BUG: Ambiguous time throws ambiguous error but then does not allow remediation with fold argument
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [ ] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd
start_date = "2021-11-07T01:00:00"
tz = "America/Denver"
start_date = int(pd.Timestamp(start_date, tz=tz).timestamp(), fold=1)
```


### Issue Description

The above code throws the following error. 

ValueError: Cannot pass fold with possibly unambiguous input: int, float, numpy.datetime64, str, or timezone-aware datetime-like. Pass naive datetime-like or build Timestamp from components.

start_date with the tz is ambiguous, and it is a naive datetime-like.

### Expected Behavior

 Instead of this error, pd.Timestamp should fold the time to the second occurrence of Nov 7th 1am

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python           : 3.8.9.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.6.0
Version          : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.4
numpy            : 1.21.4
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.3.1
setuptools       : 49.2.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
