Logistic Regression is a widely used statistical method in machine learning for binary classification problems. Unlike linear regression, which predicts continuous outcomes, logistic regression predicts the probability of a categorical outcome, typically represented as 0 or 1. This technique is particularly useful in scenarios such as determining whether an email is spam or not, or predicting if a customer will default on a loan. The model operates by estimating the relationship between independent variables and the log odds of the dependent variable, making it a powerful tool for decision-making in various fields, including finance, healthcare, and marketing.