Unsupervised learning is one of the most intriguing methods of learning that is widely being researched. Using unsupervised learning, the machine would be able to group or cluster a given dataset, but without any labels. This is helpful, especially when the machine is handling large volumes of data. The machine won't know what the data is (as there are no labels) but would be able to cluster the data based on similar or dissimilar features.

Unsupervised learning is more useful in real life as it requires less or no human intervention compared to supervised learning. Unsupervised learning can sometimes act as an initial step for supervised learning problems. Unsupervised learning is useful in applications such as recommendation systems on the web, which provide recommendations based on user interest or analysis in a retail scenario where retail giants can forecast a product's need based on sales numbers.