A Gaussian Mixture Model (GMM) is a probabilistic model that assumes that all data points are generated from a mixture of several Gaussian distributions with unknown parameters. Each Gaussian component represents a cluster, and the overall model is a weighted sum of these Gaussian distributions. GMMs are highly versatile and can approximate any continuous distribution given enough components.
