Fix typo in OpenVINO-ExecutionProvider.md (#17026)

### Description
Fixed typo (alvailable -> available) in OpenVINO-ExecutionProvider.md
file.



### Motivation and Context
This change will make the reading experience of docs better.

docs/execution-providers/OpenVINO-ExecutionProvider.md

@@ -249,7 +249,7 @@ The following table lists all the available configuration options and the Key-Va
 | device_id   | string | Any valid OpenVINO device ID | string | Selects a particular hardware device for inference. The list of valid OpenVINO device ID's available on a platform can be obtained either by Python API (`onnxruntime.capi._pybind_state.get_available_openvino_device_ids()`) or by [OpenVINO C/C++ API](https://docs.openvino.ai/latest/classInferenceEngine_1_1Core.html). If this option is not explicitly set, an arbitrary free device will be automatically selected by OpenVINO runtime.|
 | num_of_threads | string | Any unsigned positive number other than 0 | size_t | Overrides the accelerator default value of number of threads with this value at runtime. If this option is not explicitly set, default value of 8 is used during build time. |
 | cache_dir | string | Any valid string path on the hardware target | string | Explicitly specify the path to save and load the blobs enabling model caching feature.|
-| context | string | OpenCL Context | void* | This option is only alvailable when OpenVINO EP is built with OpenCL flags enabled. It takes in the remote context i.e the cl_context address as a void pointer.|
+| context | string | OpenCL Context | void* | This option is only available when OpenVINO EP is built with OpenCL flags enabled. It takes in the remote context i.e the cl_context address as a void pointer.|
 | enable_opencl_throttling | string | True/False | boolean | This option enables OpenCL queue throttling for GPU devices (reduces CPU utilization when using GPU). |
 | enable_dynamic_shapes | string | True/False | boolean | This option if enabled works for dynamic shaped models whose shape will be set dynamically based on the infer input image/data shape at run time in CPU. This gives best result for running multiple inferences with varied shaped images/data. |