Cross-lingual natural language processing is a subfield of natural language processing concerned with developing computational methods and models that enable the processing, understanding, and generation of human language across multiple distinct languages. It constitutes a significant research area focused on overcoming linguistic barriers in computational language tasks. This field investigates methodologies for transferring linguistic knowledge or models from one language to another, aligning linguistic data across languages, and building language technologies that function effectively irrespective of the input language, particularly addressing challenges posed by linguistic diversity and resource scarcity. Its significance lies in enabling global information access, facilitating communication across linguistic boundaries, and expanding the reach of language technology beyond dominant languages.