A Gaussian Mixture Model (GMM) is a probabilistic model that represents a distribution of data as a combination of multiple Gaussian distributions, each defined by its own mean and variance. It is commonly used for clustering and density estimation, allowing for the modeling of complex data distributions by capturing subpopulation characteristics within the overall dataset.