Unsupervised models

Clustering - grouping observations into similar groups or clusters (e.g. customer or market segmentation)

Anomaly detection - detecting which observations fall out of the discovered "regular pattern" and use it as an input in supervised learning or a business input

Recommender engines - e.g. recommending products or services to customers based on their similarity to other customers e.g. Netflix movie recommendations