When there is no label data, unsupervised learning techniques help in understanding the data by visualizing and compressing. The two commonly-used techniques in unsupervised learning are:

• Clustering 
• Dimensionality reduction

Clustering helps in grouping all similar data points together. Dimensionality reduction helps in reducing the number of dimensions, so that we can visualize high-dimensional data to find any hidden patterns.