Supervised learning is a type of machine learning algorithm that uses a known dataset (labeled data) to make predictions. Supervised learning algorithms learn from the data and then apply what they have learned to new data. For example, a supervised learning algorithm could be used to classify images of dogs and cats.
Unsupervised learning is a type of machine learning algorithm that makes inferences from datasets consisting of input data without labeled responses. Unsupervised learning algorithms are used to find patterns and relationships in data. For example, an unsupervised learning algorithm could be used to cluster a set of documents into topics.