The Probit Model is a type of regression used in statistics to model binary outcome variables, where the probability of a particular outcome is determined by a cumulative normal distribution function. It is particularly useful when the underlying latent variables are assumed to follow a normal distribution, offering an alternative to the logistic regression model with its own unique properties and interpretations.