Pre-trained models are neural networks that have been previously trained on a large dataset and can be fine-tuned for specific tasks, significantly reducing the computational resources and time required for model development. They leverage transfer learning, allowing the knowledge gained from solving one problem to be applied to different but related problems, enhancing performance and efficiency.