Nanophotonics has been extensively studied with the aim of unveiling and exploiting light-matter interactions that occur at a scale below the diffraction limit of light, and recent progress made in experimental technologies--both in nanomaterial fabrication and characterization--is driving further advancements in the field. From the viewpoint of information, on the other hand, novel architectures, design and analysis principles, and even novel computing paradigms should be considered so that we can fully benefit from the potential of nanophotonics. This paper examines the information physics aspects of nanophotonics. More specifically, we present some fundamental and emergent information properties that stem from optical excitation transfer mediated by optical near-field interactions and the hierarchical properties inherent in optical near-fields. We theoretically and experimentally investigate aspects such as unidirectional signal transfer, energy efficiency and networking effects, among others, and we present their basic theoretical formalisms and describe demonstrations of practical applications. A stochastic analysis of light-assisted material formation is also presented, where an information-based approach provides a deeper understanding of the phenomena involved, such as self-organization. Furthermore, the spatio-temporal dynamics of optical excitation transfer and its inherent stochastic attributes are utilized for solution searching, paving the way to a novel computing paradigm that exploits coherent and dissipative processes in nanophotonics.