Natural language processing systems understand human language by employing a combination of machine learning, tokenization, and syntactic parsing. These systems break down sentences into manageable parts, analyzing the meaning behind words and their relationships. Algorithms process large datasets to learn language patterns and context, enhancing their comprehension capabilities. Additionally, semantic analysis aids in grasping the intent behind phrases. Through these techniques, NLP systems can generate responses, perform translations, and even engage in conversation, making them increasingly effective in various applications.