Recommender engines can leverage both supervised and unsupervised learning . For instance, they rely on supervised learning to handle labeled data, such as product ratings. However, they can also use k-means clustering, an unsupervised learning algorithm, to make inferences from data sets without labels and aggregate data points with certain similarities.