BUG: .equals method returns true when comparing floats with dtype object to None 
### 

- [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.

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


### Reproducible Example

```python
import numpy as np
import pandas as pd

left = pd.Series([-np.inf, np.nan, -1.0, 0.0, 1.0, 10 / 3, np.inf], dtype=object)
right = pd.Series([None] * len(left))

print(pd.DataFrame(dict(left=left, right=right)))
print(f"{left.equals(right)=}")
print(f"{right.equals(left)=}")
```


### Issue Description

If one constructs a Series `left` containing floating-point data, but declared as dtype `object`, and another Series `right` of the same length, containing only `None`, then `left.equals.right` returns `True`, even though the two series are demonstrably not equal.

Making the comparison the other way round (i.e. `right.equals(right)`) returns `False` as is semantically correct.

Some preliminary testing brings up the following conditions for the bug to occur:

- `left` can consist of any combination of float values - including `+/-inf`, `NaN`, and both integral and fractional floats
- If `left` contains values of any other type, the `.equals` call will correctly return `False` - this includes ints and `None` itself
- The bug seems to occur with DataFrames as well - calling `.to_frame()` on both sides before calling `.equals()` has the same results. 
- The bug seems to have been introduced in pandas 1.3.0. I have observed it to occur in 1.3.0 and 1.3.4, and it does not occur on 1.2.5. 
- The bug occurs in both WSL and (ARM) macOS environments - I haven't tested on other platforms.

### Expected Behavior

`left.equals(right)` should return `False`.

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python           : 3.9.7.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.4.0-19041-Microsoft
Version          : #1237-Microsoft Sat Sep 11 14:32:00 PST 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.4
numpy            : 1.21.3
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 20.3.4
setuptools       : 58.2.0
Cython           : 0.29.24
pytest           : 6.2.5
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.2
IPython          : 7.28.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.3
numexpr          : 2.7.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 5.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.7.1
sqlalchemy       : 1.3.24
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
