Bidirectional training is an advanced learning approach that involves training models to understand and generate content in both forward and backward sequences, enhancing their comprehension and predictive capabilities. This method is particularly effective in natural language processing, where it allows models to capture context from both past and future words in a sentence, leading to more accurate and nuanced understanding.