We follow the Peng/Donoho/Clarebout definitions and consider reproducibility to be same data + same methods = same results, while replication involves new data and isomorphic methods. Rokem, Marwick, and Staneva provide a nice overview of debate around term use in their chapter in The Practice of Reproducible Research.
More specifically, Code Ocean is (first and foremost) a platform for computational reproducibility, what Kitzes calls the ability to “recreate the final reported results of the project, including key quantitative findings, tables, and figures, given only a set of files and written instructions.” Stodden distinguishes computational from statistical and empirical reproducibility, all three of which are complementary; as Zelner notes, computational reproducibility, the ability to recreate “analyses using the exact same input data ... is a necessary precondition to the new-data replication.”
Code Ocean also facilitates replication. All published capsules will accept new data and changes to the code (which will not affect the publicly accessible version, but rather create a private edition whose edits only you can see). Authors who create an interface with data selection as an input make this especially straightforward. For an example, see this published capsule, which you can test on an input video of your own.
For a thorough overview, see Barba (2018) Terminologies for Reproducible Research.