BUG: DataFrame.drop - Tuple Cannot Be Used as List-Like
- [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.

---

#### Code Sample

```python
import pandas as pd

data = {"column_a": [5, 10, 15], "column_b": ["five", "ten", "fifteen"]}
index = [0, 1, 2]
frame = pd.DataFrame(data, index=index)

frame.drop(tuple([0, 1]))
```

#### Problem description

DataFrame.drop (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html) should take a parameter 'labels' of 'single label or list-like' for the 'Index or column labels to drop.'  

According to documentation for api.types.is_list_like (https://pandas.pydata.org/docs/reference/api/pandas.api.types.is_list_like.html) "Objects that are considered list-like are for example Python lists, tuples, sets, NumPy arrays, and Pandas Series."

We should be able to drop using a Tuple of Index labels.  However, this leads to a 'KeyError' indicating the the entire tuple is not found as a value in the Index.

#### Expected Output
I expect this should return a DataFrame with the dropped Indexes - the same as if dropping with a List, Set, Array or Series of [0, 1].

```python
frame.drop(tuple([0, 1])) == frame.drop([0, 1])
```

```
expected_data = {"column_a": [15], "column_b": ["fifteen"]}
expected_index = [2]
expected_output = pd.DataFrame(data, index=index)
```

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

<details>


INSTALLED VERSIONS
------------------
commit           : 71f01a885f51544b4d9f388162d0476686061175
python           : 3.8.10.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Mon Apr 12 20:57:45 PDT 2021; root:xnu-6153.141.28.1~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.4.0.dev0+310.g71f01a885f
numpy            : 1.21.1
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 21.1.3
setuptools       : 52.0.0.post20210125
Cython           : 0.29.24
pytest           : 6.2.4
hypothesis       : 6.14.4
sphinx           : 4.1.2
blosc            : 1.10.4
feather          : None
xlsxwriter       : 1.4.4
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.0.1
IPython          : 7.25.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 2021.05.0
fastparquet      : 0.6.3
gcsfs            : 2021.05.0
matplotlib       : 3.4.2
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 4.0.1
pyxlsb           : None
s3fs             : 2021.05.0
scipy            : 1.7.0
sqlalchemy       : 1.4.22
tables           : 3.6.1
tabulate         : 0.8.9
xarray           : 0.18.2
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.53.1

</details>
