A Convolutional Neural Network (CNN) is a type of artificial neural network that is specifically used for image recognition and tasks that involve the processing of pixel data. CNNs are a subset of machine learning and are highly suitable for computer vision (CV) tasks and for applications where object recognition is vital, such as self-driving cars and facial recognition. The key component of a CNN is the convolutional layer, where filters are applied to the input image to extract features such as edges, textures, and shapes. The output of the convolutional layers is then passed through pooling layers, which are used to down-sample the feature maps, reducing the spatial dimensions while retaining the most important information. CNNs have multiple hidden layers that help in extracting information from an image, and the four important layers in CNN are the input layer, convolutional layer, pooling layer, and fully connected layer.