Human-Machine Collaboration (HMC) is a pivotal manifestation of collective intelligence in the digital age, where the synergistic interaction of humans, machines, and physical systems drives socio-economic evolution. This paper redefines HMC through the lens of co-evolution of human and machine capabilities and distributed decision-making, systematically analyzing its development history, collaboration models, and transformative impact on productivity, innovation, and labor markets. This paper believes that human-machine collaboration is the collaborative participation of people and machines in solving problems. It introduces various models of human-machine collaboration from the perspective of automation and autonomy, and discusses the criteria for selecting appropriate models. In terms of economic and social impact, this article first summarizes the existing quantitative measurement methods at the national, regional, and enterprise levels, and discusses the economic impact and impact path of human-machine collaboration from the micro, market, and macro levels of individuals and enterprises. Finally, this paper proposes future research directions, including the improvement of quantitative data of human-machine collaboration, the clarification of the issue of legal responsibility, the formulation of management-level strategies, and in-depth research in the fields of medical care, aviation, banking, etc. This paper aims to deepen the understanding of human-machine collaboration and provide reference for future research.