A Feed-Forward Neural Network is a type of artificial neural network where connections between the nodes do not form a cycle, allowing information to flow in only one direction—from input to output. This architecture is primarily used for supervised learning tasks, such as classification and regression, and is the simplest form of neural networks, making it foundational for understanding more complex architectures.