BUG: Index and MultiIndex ops treating nan differently
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

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

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

``Index.union`` treats ``nan`` differently than ``MultiIndex.union``. Same goes for intersection. 

```python
idx1 = Index([1, np.nan])
idx2 = Index([1, np.nan, 3])

idx1.union(idx2)
idx1.intersection(idx2)

mi1 = MultiIndex.from_arrays([[1, np.nan]])
mi2 = MultiIndex.from_arrays([[1, np.nan, 3]])
mi1.union(mi2)
mi1.intersection(mi2)

```

Output:
```
Float64Index([1.0, 3.0, nan], dtype='float64')
Float64Index([1.0, nan], dtype='float64')
MultiIndex([(1.0,),
            (nan,),
            (nan,),
            (3.0,)],
           )
MultiIndex([(1.0,)],
           )
```

#### Problem description

Inconsistent behavior is a problem. Additionally if both MultiIndexes are *equal* nan is only returned once. When not matching nan is the desired output, we have to adjust for theses cases before checking for equality. 

#### Expected Output

I am not quite sure what to expect, but taking the current behavior of merges into account, I think it would be more reasonable to return
```
MultiIndex([(1.0,),
            (nan,),
            (3.0,)],
           )
MultiIndex([(1.0,),
            (nan,)],
           )
```

for the MultiIndex operations. Thoughts @jbrockmendel ?

related to #38439

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : c6b05c3ad771da775011647f66687a398e11c533
python           : 3.8.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-58-generic
Version          : #64-Ubuntu SMP Wed Dec 9 08:16:25 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0.dev0+129.gc6b05c3ad7
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 49.6.0.post20201009
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : 5.37.1
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.3
fastparquet      : 0.4.1
gcsfs            : 0.7.1
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : 2.0.0
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.5.2
sqlalchemy       : 1.3.20
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.51.2
None

Process finished with exit code 0


</details>
