Masked Language Models (MLMs) are a type of neural network architecture used in natural language processing where parts of the input text are masked or hidden, and the model learns to predict these masked tokens based on their context. This approach enables the model to gain a deep understanding of language semantics and syntactic structures, making it effective for tasks like text completion, translation, and sentiment analysis.