The rapid adoption of Artificial Intelligence (AI), Machine Learning (ML), predictive analytics, and automation has transformed Human Resource Management (HRM), leading to the emergence of Algorithmic Human Resource Management (Algorithmic HRM). Organizations increasingly use algorithm-driven systems to support recruitment, performance management, workforce planning, employee engagement, learning and development, and compensation decisions. These technologies enhance efficiency, accuracy, and strategic decision-making while improving overall organizational performance. Despite these benefits, Algorithmic HRM presents important ethical challenges, including concerns related to transparency, fairness, accountability, privacy, employee surveillance, and algorithmic bias. As organizations become more dependent on intelligent technologies, addressing these ethical issues is essential for maintaining employee trust and organizational sustainability. The emergence of Industry 5.0 has shifted the focus from technology-centered automation to human-centric innovation, emphasizing collaboration between humans and intelligent systems. In this context, ethical sustainability provides a framework for ensuring that technological advancements support both organizational objectives and employee well-being.This chapter explores the evolution and applications of Algorithmic HRM within Industry 5.0 environments and examines the ethical implications of algorithm-driven workforce management. It highlights the importance of human–machine collaboration and proposes an Ethical Sustainability Framework based on fairness, transparency, accountability, human oversight, and employee well-being. The chapter contributes to the growing discussion on responsible AI adoption and demonstrates how Algorithmic HRM can support innovation, workforce resilience, and sustainable organizational development in the era of Future-Ready India.