FAIR data and open data are different, although there are similarities.
The key difference is that open data should be available to everyone to access, use, and share, without licences, copyright, or patents. It is expected that open data at most should be subject to attribution/share-alike licenses.
FAIR data, however, uses the term “Accessible” to mean accessible by appropriate people, at an appropriate time, in an appropriate way. This means that data can be FAIR when it is private, when it is accessible by a defined group of people, or when it is accessible by everyone (open data). It depends completely on the purpose of the data, where the data currently is in its lifecycle, and the end-usage of the data. For example, new experimental data may only be accessible by the generator and their group to start, then with consortia partners as the findings become refined, and finally with the public upon publication. Personally sensitive data may never be publicly accessible and usable. Commercially sensitive data may be held privately for stretches of time after collection and interpretation. Users are also free to use more restrictive licenses to govern how the data may be reused.
FAIR also explicitly includes other characteristics:
Findable: where data should be able to be found by appropriate people at appropriate times. This can include shared folders, drives, private databases, public databases or more. It really depends on what part of the data life cycle the data is currently in. The data will likely transition through a few of these different options during its lifecycle.
Interoperable/Re-usable: these characteristics refer more to how the data is formatted (e.g. standard formatting), whether the software for interpreting/interrogating/using the data is available (e.g. freely, with a license etc.
Source: Ask Open Science