The multivariate Gaussian distribution is a generalization of the one-dimensional normal distribution to higher dimensions, where random variables are characterized by a mean vector and a covariance matrix. It is crucial in statistics and machine learning for modeling the joint distribution of multiple correlated variables, and is widely used in fields such as pattern recognition, finance, and natural language processing.