Pre-trained language models are neural network models trained on large corpora of text data to understand and generate human language, allowing them to be fine-tuned for specific tasks such as translation, summarization, and sentiment analysis. These models leverage transfer learning to improve performance and reduce the amount of labeled data needed for downstream tasks.