The proliferation of Internet of Things (IoT) devices presents challenges for data transmission efficiency, including network congestion and data retrieval latency. Named Data Networking (NDN), a key architecture within Information-Centric Networking (ICN), has proven to be a promising solution to these issues through in-network caching. Unlike traditional ICN, IoT data traffic exhibits distinct characteristics in terms of content popularity dynamics and freshness requirements due to the diversity of IoT application scenarios. Efficient caching of IoT data becomes challenging due to the need to balance both the popularity and freshness of content, as popular items may quickly become outdated, and fresh content is often only relevant for a limited period. In this paper, we propose Auction-Based Caching Decision (ABCD) Algorithm, a caching strategy for IoT data traffic which simultaneously considers content popularity and freshness to prioritize caching of high-demand and timely content. ABCD utilizes an auction mechanism whereby content bids to be cached based on a combined recency-frequency and freshness-aware criteria. Simulation results using NDNsim demonstrate significant improvements in cache hit ratio, data retrieval latency, and content freshness in comparison with LCE, LCD, ProbCache and CFPC.