Latent Variable Models are statistical models that include variables that are not directly observed but are inferred from other variables that are observed. These hidden variables, known as latent variables, help explain relationships in the data and can represent concepts like intelligence or satisfaction that are difficult to measure directly. These models are widely used in various fields, including psychology, sociology, and economics, to analyze complex data structures. By capturing the underlying factors that influence observed data, Latent Variable Models provide insights into patterns and relationships that might not be apparent through direct observation alone.