API: support "unique=True" in MultiIndex.get_level_values()
#### Code Sample, a copy-pastable example if possible

I often find my self doing
```python
In [2]: df = pd.Series(index=pd.MultiIndex.from_product([['A', 'B'], ['a', 'b']]))

In [3]: df.index.get_level_values(0).unique()
Out[3]: Index(['A', 'B'], dtype='object')
```

#### Problem description

The above is very inefficient, because first a ``Series`` is built which includes a copy of the entire level (possibly using way more memory than the index itself), and only then duplicates are stripped. [Other people on SO](https://stackoverflow.com/questions/24495695/pandas-get-unique-multiindex-level-values-by-label#comment44836216_24496435) have faced the same problem, and this is also blocking a fix I wrote for #17845.

I'm pushing a simple PR in seconds.

#### Expected Output

Same as above, but in an efficient way.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-3-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.21.0rc1+19.gb15d92d14
pytest: 3.0.6
pip: 9.0.1
setuptools: None
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.1.0.dev
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: None
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1

</details>
