The Multivariate Normal Distribution is a statistical distribution that generalizes the concept of a normal distribution to multiple variables. It describes how a set of variables can vary together, characterized by a mean vector and a covariance matrix. Each variable in the distribution can be thought of as a dimension in a multi-dimensional space. This distribution is important in various fields, including statistics, finance, and machine learning, as it helps model relationships between multiple correlated variables. When the variables are normally distributed, their joint behavior can be analyzed using this distribution, making it a fundamental concept in multivariate analysis.