A baseline model in machine learning is a simple, often basic model used as a reference point to compare the performance of more complex models developed during the project. It sets a minimum performance threshold, ensuring that newer, more sophisticated models actually provide a significant improvement over simple approaches. Baseline models are typically easy to implement and understand, such as using the mean of the target variable for regression tasks or the most frequent class for classification tasks. Establishing a baseline is crucial for evaluating the effectiveness and value of machine learning models in solving a specific problem.