The exponential growth of the Internet of Everything (IoE) demands secure, intelligent access control mechanisms to manage data flow and device interaction efficiently. This paper proposes a novel architecture that integrates post-quantum cryptography, federated learning, and explainable AI to ensure privacy-preserving, real-time decision-making for resource-constrained IoE environments. The edge nodes, equipped with lightweight cryptographic engines and context-aware training modules, perform preliminary data processing and secure communication via GG-ULL and PQCrypto protocols. The cloud leverages federated learning to train distributed models and uses a multi-agent policy engine for dynamic access decisions. Blockchain-backed audit trails ensure accountability, while the explainable AI module enhances transparency in access control. The system supports mission-critical services like SCADA and health data lakes, guaranteeing secure and interpretable decision flows. This architecture paves the way for resilient, scalable, and intelligent access control frameworks suitable for next-generation IoE ecosystems.