Unsupervised machine learning algorithms infer patterns from a dataset without using known or labeled outcomes as a guide. Unsupervised machine learning methods cannot be applied directly to a regression or classification problem because you have no idea what the values for the output data might be, making it impossible to train the algorithm normally. Unsupervised learning, on the other hand, can be used to uncover the underlying structure of the data.