Unsupervised Learning is a type of ML where the model is completely data-driven. A typical example of an unsupervised learning task is automatically clustering documents. The model is unsupervised so it learns how to cluster based on patterns that exist within the data itself. Unsupervised learning is attractive for many applications because of the low barrier to entry. All that is needed is the raw dataset. It doesn’t require data to be labelled by humans.